Space-based radio signals are used extensively for atmospheric monitoring. As these signals propagate from their space-based transmitters to the earth, the atmosphere induces phase shifts, group delays, and amplitude variations. A receiver which processes these signals in an appropriate fashion can extract an estimate of these phase, delay and amplitude variations and can, in turn, infer some information about the atmosphere. Global Navigation Satellite System (GNSS) signals are widely used for this purpose, due both to their abundance, their global coverage, and the fact that they are transmitted at more than one frequency. The ionosphere and troposphere are monitored using these signals as they both induce propagation speed and direction changes to signals transmitted in the L-band.
To measure these effects, GNSS receivers are employed. These receivers track the carrier frequency and phase and the modulated ranging-code of these signals and produce measurements of the signal power, the carrier phase and the ranging-code delay. These values, hereafter referred to as raw signal measurements, are then used to calculate various properties relating to the signal propagation through the atmosphere, hereafter referred to as atmosphere-measurements. Conventionally, to produce these raw signal measurements the receiver performs a closed-loop tracking of the parameters of interest, and typical systems include the use of a Delay-Lock Loop (DLL) for the ranging-code and a Phase-Lock Loop (PLL) for the carrier. Although many other systems are available, in general, receivers rely on some sort of recursive feed-back/feed-forward mechanism to produce the raw signal measurements.
The calculation of atmosphere-measurements is dependent upon both the availability and the quality of the raw signal measurements. Thus, when the receiver tracking algorithms experience difficulty in accurately tracking the signal parameters, the quality of the resultant atmosphere-measurements is reduced. The particular implementation of the tracking algorithm also has an impact on the resultant atmosphere-measurements; for example, filtering effects or transient errors within the tracking algorithms can produce artefacts in the atmosphere-measurements.
Atmospheric anomalies (for example, ionospheric scintillation) can cause difficulties for a receiver's tracking algorithm, and when a receiver is used to measure this anomaly the atmosphere-measurements can be significantly degraded in quality, due to either degraded quality of the raw signal measurements or due to their unavailability, when the tracking algorithms fail. Many techniques used to improve receiver tracking robustness and measurement availability, such as extended integration times and reduced tracking bandwidths, also contribute to a degradation of the raw signal measurements and, ultimately, result in artefacts in the atmosphere-measurements.
The generation of certain atmosphere-measurements including, for example, the ionospheric measurement known as sigma-phi (σφ), necessitates a filtering of the raw signal measurements. This filtering stage, often known as a de-trending, has a significantly long convergence time. When intermittent unavailability of raw signal measurements occurs, the resultant unavailability of the atmospheric-measurements can be far longer.
A weakness in the contemporary approaches is the estimation stage. Raw signal parameters are estimated or tracked by the receiver prior to being used to compute the atmosphere-measurements. This tracking stage is problematic when non-ideal conditions prevail. The drawbacks of conventional systems will be discussed in relation to FIGS. 1 and 2 (PRIOR ART), while addressing some theoretical factors.
Typically the GNSS signal received at the antenna of a ground-based receiver is modelled as:
                                                                        r                ⁡                                  (                  t                  )                                            =                            ⁢                                                                    ∑                                          i                      ∈                                              S                        sig                                                                              ⁢                                                            s                      i                                        ⁡                                          (                      t                      )                                                                      +                                  n                  ⁡                                      (                    t                    )                                                                                                                                                                                s                    i                                    ⁡                                      (                    t                    )                                                  =                                ⁢                                                                            2                      ⁢                                                                                          ⁢                                                                        P                          i                                                ⁡                                                  (                          t                          )                                                                                                      ⁢                                                            d                      i                                        ⁡                                          (                                              t                        -                                                                              τ                            i                                                    ⁡                                                      (                            t                            )                                                                                              )                                                        ⁢                                                            c                      i                                        ⁡                                          (                                              t                        -                                                                              τ                            i                                                    ⁡                                                      (                            t                            )                                                                                              )                                                        ⁢                                      sin                    ⁡                                          (                                                                                                    ω                            i                                                    ⁢                          t                                                +                                                                              θ                            i                                                    ⁡                                                      (                            t                            )                                                                                              )                                                                                  ,                                                          (        1        )            where Ssig is the set of satellite signals in view, si (t) denotes the ith signal received from the visible satellites and n (t) denotes the additive thermal noise. The various parameters in Eq. (1) represent the following signal properties: Pi is the total received signal power in watts; ωi is the nominal RF carrier frequency in units of rad/s; di (t) represents the bi-podal data signal or secondary code; ci (t) is the signal spreading sequence and sub-carrier; θi (t) is the total received phase process including propagation delays, satellite-to-user dynamics, atmospheric effects and satellite clock effects; the process τi (t) represents the total delay observed at the receiver, including propagation delay, satellite clock effects and atmospheric delays.
In particular, the carrier phase term, θi (t) in Eq. (1) represents a number of distinct phase processes. Mathematically, it can be represented as the linear combination:θi(t)=θ0+θLOS(t)+θSV Clk.(t)+θAtm.(t)  (2)where θ0 represents some arbitrary initial phase, θLOS (t) represents the phase process induced by the line-of-sight geometry/dynamics between the satellite and the receiver, θSV Clk. (t) represents the phase process induced by errors in the satellite clock, and θAtm. (t) represents the phase process induced by the atmosphere through which the signal propagates.
FIG. 1 (PRIOR ART) is a block diagram of the Digital Matched Filter 102-1 of a conventional receiver, illustrating how the local estimates of carrier phase ({circumflex over (θ)}i) and ranging-code delay (i) are used to generate the correlator values Yi [n].
A GNSS receiver will, generally, implement a down-conversion of the received RF signal to a zero or non-zero IF and subsequently sample the signal. These signal samples (r) are then processed by a Digital Matched Filter (DMF) 102-1 which implements the following operation:
                                          Y            i                    ⁡                      [            n            ]                          =                              1                          T              I                                ⁢                                    ∑                              m                =                                  n                  ⁢                                                                          ⁢                                                            T                      I                                                              T                      s                                                                                                                                        (                                          n                      +                      1                                        )                                    ⁢                                                            T                      I                                                              T                      s                                                                      -                1                                      ⁢                                          r                ⁡                                  (                                      mT                    S                                    )                                            ⁢                                                c                  i                                ⁡                                  (                                                                                    τ                        ^                                            i                                        ⁡                                          (                                              mT                        S                                            )                                                        )                                            ⁢                              e                                                      -                                          j                      ⁡                                              (                                                                                                            ω                              i                                                        ⁡                                                          (                                                              mT                                s                                                            )                                                                                +                                                                                                                    θ                                ^                                                            i                                                        ⁡                                                          (                                                              m                                ⁢                                                                                                                                  ⁢                                                                  T                                  s                                                                                            )                                                                                                      )                                                                              ,                                                                                        (        3        )            where the variables i and {circumflex over (θ)}i are the receiver's estimate of the variables τi and θi, as defined in Eq. (1), and the term Yi[n] is known as the correlator value.
The operation described by Eq. (3) is implemented in the receiver in its tracking algorithm as part of the carrier phase and ranging-code phase tracking loops.
FIG. 2 (PRIOR ART) is a block diagram of a typical closed-loop tracking architecture depicting a loop for both a carrier tracking loop 104 and a ranging-code tracking 106. As will be appreciated by persons skilled in the art, a DMF bank 102 incorporates a plurality of instances 102-1, 102-2, 102-3 (i.e. one per channel; here, only three are shown).
A typical implementation follows the block diagram presented in FIG. 2, whereby the correlator values, Yi[n], are processed by the carrier tracking block 104 and ranging-code tracking block 106 to produce estimates of the signal parameters, i (mTS) and {circumflex over (θ)}i (mTs), which, in turn, are used to generate the subsequent set of correlator values Yi[n].
The particular algorithms which are used to estimate properties and attributes of the atmosphere through which the GNSS signals have propagated are implemented in the block entitled ‘Atmospheric Monitoring Algorithms’ 108. These algorithms operate on the following quantities: Yi[n], as generated by the DMF 102 and i and {circumflex over (θ)}i which are estimated by the tracking algorithms. The performance of the monitoring algorithms is directly influenced by the quality of the raw signal measurements and so correct operation of both the carrier and ranging-code tracking algorithms is crucial to atmospheric monitoring receivers. A problem is that under high atmospheric activity conditions variations in the propagation channel can be such that these tracking algorithms can perform poorly or fail.
YORK J ET AL: “Development of a Prototype Texas Ionospheric Ground Receiver (TIGR)”, ITM 2012—PROCEEDINGS OF THE 2012 INTERNATIONAL TECHNICAL MEETING OF THE INSTITUTE OF NAVIGATION, THE INSTITUTE OF NAVIGATION, 8551 RIXLEW LANE SUITE 360 MANASSAS, Va. 20109, USA, 1 Feb. 2012 (2012-02-01), pages 1526-1556, XP056000936, discloses a software receiver designed to make ionospheric measurements from satellite signals. RF data is directly sampled via a 2 Gigasample/s ADC and passed to an FPGA, where it is digitally filtered, and down-sampled into three tunable bands, each with a bandwidth of 20 MHz. A reduced digital data stream is passed to a second FPGA, where the individual channels are filtered into multiple narrow signal bands, centered on the frequency of the satellite signal as adjusted to compensate for the predicted Doppler shift. Estimation of the phase and amplitude of the signal in this data is accomplished by the use of onboard software running on a general purpose CPU.
LULICH T D ET AL: “Open Loop Tracking of Radio Occultation Signals from an Airborne Platform”, GNSS 2010—PROCEEDINGS OF THE 23RD INTERNATIONAL TECHNICAL MEETING OF THE SATELLITE DIVISION OF THE INSTITUTE OF NAVIGATION (ION GNSS 2010), THE INSTITUTE OF NAVIGATION, 8551 RIXLEW LANE SUITE 360 MANASSAS, Va. 20109, USA, 24 Sep. 2010 (2010-09-24), pages 1049-1060, XP056000217, discloses a radio occultation (RO) based remote sensing technique that uses signals from the Global Positioning System (GPS) to determine electron density in the ionosphere, using an open loop (OL) tracking method employing a model-based estimate of Doppler frequency and a record of the GPS data bits.
G. BEYERLE ET AL: “Observations and simulations of receiver-induced refractivity biases in GPS radio occultation”, JOURNAL OF GEOPHYSICAL RESEARCH, vol. 111, no. D12, 1 Jan. 2006 (2006-01-01), XP055158431, ISSN: 0148-0227, DOI: 10.1029/2005J D006673 discloses observations and simulations of receiver-induced refractivity biases in GPS radio occultation.
NIU F ET AL: “GPS Carrier Phase Detrending Methods and Performances for Ionosphere Scintillation Studies”, ITM 2012—PROCEEDINGS OF THE 2012 INTERNATIONAL TECHNICAL MEETING OF THE INSTITUTE OF NAVIGATION, THE INSTITUTE OF NAVIGATION, 8551 RIXLEW LANE SUITE 360 MANASSAS, Va. 20109, USA, 1 Feb. 2012 (2012-02-01), pages 1462-1467, XP056000934, discloses GPS carrier phase detrending methods and performances for ionosphere scintillation studies. The detrending makes use of a 6th order Butterworth filter.
The present invention further seeks to produce atmospheric measurements derived from raw signal measurements of radionavigation (e.g. GNSS) signals which are generated in a purely open-loop manner.
The present invention seeks to generate atmospheric measurements even in circumstances of poor quality raw signal measurements and/or high atmospheric activity.